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A Continuous Registry of Medical Record, Patient Input, and Epidemiological Data of Patients With Ulcerative Colitis:
Katsuyoshi Matsuoka1, Shuji Hibiya2, Katsuyoshi Ando3
1Division of Gastroenterology and Hepatology, Department of Internal Medicine, Toho University Sakura Medical Center.
Background:
This registry aims to allow for a prospective non-interventional observational study of ulcerative colitis. This will facilitate monitoring of the current state of ulcerative colitis in Japan and improving the long-term disease course and adverse events associated with current treatment options.
Methods:
Inclusion of patients from five centres in Japan is planned. The study is expected to take place from July 15, 2020, to November 30, 2024. Background, demographics, and medical history/information will be collected from electronic medical records at enrolment. Medical information including medications, laboratory data, and disease activity will be collected automatically from electronic medical records throughout the study. Patient-reported quality of life data will be collected directly from patients via smartphone. Efficacy endpoints (clinical remission rate, clinical improvement rate, and endoscopic healing rate) and safety endpoints (incidence of adverse events and specific ulcerative colitis-related events) will be collected according to treatment administered. Treatment categories include no treatment, 5-aminosalicylic acids, corticosteroids, immunomodulators, immunosuppressants, anti-tumour necrosis alpha agents, cytapheresis, Janus kinase inhibitors, anti-integrin antibodies, and anti-interleukin-12/23 antibodies.
Conclusions:
The dataset will include cross-sectional and longitudinal data and is expected to capture the state of ulcerative colitis in Japan. Patients will be included on a large scale, and the registry will be established automatically from electronic medical records and direct patient input, facilitating the accurate recording of medical information for patients with ulcerative colitis in Japan and minimizing limitations intrinsic to databases that require manual data entry, such as the burden on participating investigators and entry of data with errors/typos.
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